Product Images Gabapentin
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 4 images provide visual information about the product associated with Gabapentin NDC 61919-982 by Direct Rx, such as packaging, labeling, and the appearance of the drug itself. This resource could be helpful for medical professionals, pharmacists, and patients seeking to verify medication information and ensure they have the correct product.
640 30
This is a description of a medication called GABAPENTIN. It comes in a 300mg capsule form with 30 capsules per bottle. The NDC number is 61919-640-30, and the lot expiration date is 12119. The medication is generic for NEURONTIN. The capsules are made up of Gabapentin, USP 300mg. The dosage and storage instructions can be found in the package insert. The medication is for prescription use only and should be kept out of reach of children.*
image description - Label3
This is a description of Gabapentin medication available in 300mg capsules with 120 counts. The contact information of the manufacturing company is provided, which is possibly located in Alpharetta. Not much information is available about the medication itself.*
image description - MODULE 1
The given text appears to be a chemical formula and molecular weight of a compound. The compound's name and properties cannot be determined without additional information.*
image description - label 2
This is a bottle of Gabapentin capsules. The bottle contains 90 capsules, each containing 300mg of Gabapentin. The capsules are generic for Neurontin. The label warns that the drug is for a specific person and should not be transferred to another person. It is an RX only drug and should be kept out of the reach of children. The package insert should be consulted for dosage information, and the drug should be stored between 68-77 degrees F. There are several lot numbers and expiration dates listed, which may correspond to different batches or purchases of the drug. NDC numbers are also included.*
* The product label images have been analyzed using a combination of traditional computing and machine learning techniques. It should be noted that the descriptions provided may not be entirely accurate as they are experimental in nature. Use the information in this page at your own discretion and risk.
